Data-driven parcellations are widely used for exploring the functional organization of brain, and also reducing high dimensionality fMRI data. Despite flurry methods proposed in literature, brain not highly reproducible at level individual subjects, even with very long acquisitions. Some areas more difficult to parcellate than others, association heteromodal cortices being most challenging. An ...

The prerequisites of transition from the typology high-rise residential development dormitory districts, remote epicenter urban activity, to mixed functionality, interpreting morphological and symbolic codes metropolis historical heritage are considered. criticism modernist strategy is based on understanding functional zoning as an excessively rigid model city. historic environment with its hie...

We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various setting...